CS229 Syllabus Spring 2023 public

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1			Date	Lecture Topics	Deliverables	Notes

2	Week 1	Lecture 1	4/3/2023	Introduction		Slides
3		Lecture 2	4/5/2023	Supervised learning setup. LMS.	Problem Set 0 Released	Slides / Section 1 of Main Notes
4		TA Lecture 1	4/7/2023	Linear Algebra Review		Notes
5	Week 2	Lecture 3	4/10/2023	Weighted Least Squares. Logistic regression. Newton's Method		Slides / Section 2 of Main Notes
6		Lecture 4	4/12/2023	Exponential family. Generalized Linear Models. Multi-class classification.	Problem Set 1 Released	Slides / Section 3 of Main Notes
7			4/12/2023		Problem Set 0 (Due at 11:59 pm PT - Ungraded)
8		TA Lecture 2	4/14/2023	Probability Review		Notes; Slides
9	Week 3	Lecture 5	4/17/2023	Gaussian discriminant analysis.		Section 4.1 of Main Notes
10		Lecture 6	4/19/2023	Kernels		Section 5 of Main Notes
11			4/21/2023		Final Project Proposal (Due at 11:59 pm PT)
12		TA Lecture 3	4/21/2023	Python/Numpy		Slides; Materials
13	Week 4	Lecture 7	4/24/2023	SVM. Neural Networks.		Section 6 & 7 of Main Notes
14		Lecture 8	4/26/2023	Neural Networks 2; Architecture	Problem Set 2 Released	Sections 7.1 & 7.2 of Main Notes
15			4/26/2023		Problem Set 1 (Due at 11:59 pm PT)
16		TA Lecture 4	4/28/2023	Deep Learning		Slides; Notebook
17	Week 5	Lecture 9	5/1/2023	Neural Networks 3; Backprop		Section 7.3 of Main Notes
18		Lecture 10	5/3/2023	Bias - Variance. Regularization. Feature / Model Selection		Section 8 of Main Notes
19		TA Lecture 5	5/5/2023	Evaluation Metrics		Slides
20	Week 6	Lecture 11	5/8/2023	ML Advice.		Section 9 of Main Notes; slides (2023 version)
21		Lecture 12	5/10/2023	K-Means. GMM (non EM). Expectation Maximization.	Problem Set 3 Released	Sections 10, 11.1, 11.2 of Main Notes; slides
22			5/10/2023		Problem Set 2 (Due at 11:59 pm PT)
23			5/12/2023		Final Project Milestone (Due at 11:59 pm PT)
24		TA Lecture 6	5/12/2023	Midterm Review		Slides
25	Week 7	Lecture 13	5/15/2023	GMM. Factor Analysis.		Slides
26		Lecture 14	5/17/2023	PCA/ICA		Sections 12 & 13 of Main Notes, Slides
27			5/18/2023		MIDTERM (CEMEX, 6 pm - 9 pm PT)
28				No TA Lecture (Midterm Week)
29	Week 8	Lecture 15	5/22/2023	Weak supervised / unsupervised learning		Slides
30		Lecture 16	5/24/2023	Reinforcement Learning, policy gradients	Problem Set 4 Released	Section 15&17 of Main Notes
31			5/24/2023		Problem Set 3 (Due at 11:59 pm PT)
32			5/26/2023	No TA Lecture
33	Week 9	Lecture 17	5/29/2023	No Lecture - Memorial Day
34		Lecture 18	5/31/2023	Pre-training / foundation models / supervised learning		Section 14.3.1 of Main Notes
35			6/2/2023
36	Week 10	Lecture 19	6/5/2023	LLMs, in-context learning, prompting, instruct tuning, RLHF		Slides
37		Lecture 20	6/7/2023	Guest Lecture by Diyi Yang on Societal impact of ML
38			6/8/2023		Problem Set 4 (Due at 11:59 pm PT)
39		TA Lecture 7	6/9/2032			Notes
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42			6/12/2023		Final Project Report (Due at 11:59 pm PT)
43			6/13/2023		Final Project Poster Session (Burnham Pavilion, 3:30 pm - 6:30 pm PT)
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